User Classification Using Mobility Patterns in Macrocellular Wireless Networks

As more and more applications go mobile it's becoming increasingly important to understand user mobility patterns and network usage characteristics in wireless networks. Such an understanding would guide the design of applications geared toward mobile environments, would help improve simulation tools, by providing a more representative workload and better user mobility models, and could result in a more effective deployment of wireless network components. User mobility affects quality of service, and makes capacity planning more difficult. This paper presents an analysis of user mobility patterns in macrocellular wireless networks, based on empirical data obtained from several users. Based on mobility and degree of predictability a mobile user classification is attempted. Since prediction algorithms and simulation studies heavily rely on the user mobility characteristics, a classification of the heterogeneous user population would help to spawn a more realistic environment to study system performances.